Charlie Tan — accepted AI-conference papers

2026

Autoregressive Boltzmann Generators

Danyal Rehman, Charlie Tan, Yoshua Bengio, Joey Bose, Alexander Tong

ICML 2026spotlight

Efficient sampling of molecular systems at thermodynamic equilibrium is a hallmark challenge in statistical physics. This challenge has driven the development of Boltzmann Generators (BGs), which allow rapid generation of uncorrelated equilibrium samples by combining a generative model with exact li…

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2024

On the Limitations of Fractal Dimension as a Measure of Generalization

Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael M. Bronstein, Anthea Monod

NeurIPS 2024poster

Bounding and predicting the generalization gap of overparameterized neural networks remains a central open problem in theoretical machine learning. There is a recent and growing body of literature that proposes the framework of fractals to model optimization trajectories of neural networks, motivati…

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